Correcting pervasive errors in RNA crystallography through ......and and , –)

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models, and recommended that assessment of these features be included in PDB validation and during peer review4. There is thus a critical need for efficient algorithms that can resolve ambi-guities in existing and future RNA crystallographic models.

The difficulty of resolving RNA crystallographic errors is under-scored by limitations in currently available computational tools. RNA backbone correction (RNABC)5 and RNA constructed using rotameric nucleotides (RCrane)3 can identify and fix backbone- conformer errors in some models. However, these methods anchor phosphates and bases to starting positions determined manually and thus only correct a subset of errors. Recent advances in Rosetta RNA de novo modeling6–8 and electron density–guided protein modeling9,10 have suggested that confident, high-accuracy struc-ture prediction may be feasible if it is guided by experimental data. We present here a method termed ERRASER, which we integrated with PHENIX tools for diffraction-guided refinement. The protocol is based on exhaustively sampling each nucleotide’s possible confor-mations and on scoring by the physically realistic Rosetta energy function supplemented with an electron density correlation score (Supplementary Fig. 1). Based on a benchmark of published crys-tallographic data sets and newly solved RNA structures, we report that this automated pipeline resolves the majority of geometric errors while retaining or improving correlation to diffraction data.

To measure the effectiveness of the ERRASER-PHENIX pipeline, we collected a test set of 24 crystal structures for RNA molecules ranging from small pseudoknots to entire ribosomal subunits (Fig. 1 and Supplementary Table 1). We compared the effectiveness of our ERRASER protocol to that of RNABC and RCrane as well as PHENIX alone (Table 1). In the starting PDB-deposited structures, MolProbity tools revealed many potential errors in four classes: atom-atom steric clashes, high frequencies of outlier bond lengths or angles, ‘non-rotameric’ backbone conformations and potentially incorrect sugar puckers11. Although not all of these features are necessarily incorrect, high frequencies of such errors in medium-resolution to low-resolution

correcting pervasive errors in rna crystallography through enumerative structure predictionFang-Chieh Chou1, Parin Sripakdeevong2, Sergey M Dibrov3, Thomas Hermann3 & Rhiju Das1,2,4

three-dimensional rna models fitted into crystallographic density maps exhibit pervasive conformational ambiguities, geometric errors and steric clashes. to address these problems, we present enumerative real-space refinement assisted by electron density under rosetta (erraser), coupled to Python-based hierarchical environment for integrated ‘xtallography’ (PheniX) diffraction-based refinement. on 24 data sets, erraser automatically corrects the majority of molProbity-assessed errors, improves the average Rfree factor, resolves functionally important discrepancies in noncanonical structure and refines low-resolution models to better match higher-resolution models.

Over the last decade, progress in RNA crystallography has revealed many three-dimensional structures of functional RNAs, providing powerful information for understanding their bio-logical functions1,2. Nevertheless, RNA structures are typically solved at low diffraction resolution (>2.5 Å)3. A recent report by the Protein Data Bank (PDB) X-ray Validation Task Force noted the ubiquity of bond geometry errors, anomalous sugar puckers and backbone-conformer ambiguities in RNA crystallographic

1Department of Biochemistry, Stanford University, Stanford, California, USA. 2Biophysics Program, Stanford University, Stanford, California, USA. 3Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, California, USA. 4Department of Physics, Stanford University, Stanford, California, USA. Correspondence should be addressed to R.D. ([email protected]).Received 26 SeptembeR; accepted 30 OctObeR; publiShed Online 2 decembeR 2012; dOi:10.1038/nmeth.2262

table 1 | Average values for the validation results of the benchmark set

outlier bond (%)a

outlier angle (%)a

clash scoreb

outlier backbone

rotamer (%)c

Potentially incorrect

pucker (%)d R Rfreenucleotide

similarity (%)ePucker

similarity (%)e

PDB 0.53 1.18 18.03 18.8 5.0 0.210 0.256 64.9 91.5PHENIX 0.01 0.03 10.79 15.2 2.4 0.199 0.244 71.7 96.4RNABC-PHENIX 0.01 0 10.03 15.3 2.4 0.200 0.244 71.9 96.3RCrane-PHENIX 0.003 0.12 10.12 10.3 1.0 0.207 0.252 74.1 95.8ERRASER-PHENIX 0 0 7.04 7.9 0.2 0.199 0.244 80.5 97.0aBond lengths and angles with deviation > 4 s.d. compared to PHENIX ideal geometry11. bSerious clashes (atom pairs that have steric overlaps ≥ 0.4 Å) per 1,000 atoms11. cAssigned using RNA Ontology Consortium definition12. dDetermined using a geometric criterion based on the distance between the glycosidic bond vector (C1–N1/9) and the following (3) phosphate11. eComparison of refined low-resolution models to independent high-resolution models (supplementary table 9). Nucleotides in which the differences between all torsion angles were smaller than 40° were denoted ‘similar’. Nucleotides in which torsion angle δ agreed to within 20° were assigned ‘similar’ puckers.

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models (2.5–3.5 Å) compared to high-resolution models (4 s.d. from reference values) in the crystallographic models have mean frequencies of 0.53% and 1.18% in the starting PDB coordinates. Some of these outliers are due to different ideal bond geometries used by different refinement packages, and thus applying PHENIX alone lowered the outlier frequencies substantially. Nevertheless, application of ERRASER-PHENIX gave greater improvement, eliminating all the outlier bond lengths and angles in the bench-mark (Table 1 and Supplementary Table 2).

Second, ERRASER-PHENIX substantially reduced the steric clashes in RNA coordinates fitted into low-resolution elec-tron density. In a bacteriophage prohead RNA test case (PDB identifier 3R4F), the initial pervasive clashes were reduced by 80% with ERRASER-PHENIX (Fig. 1a). Over the entire bench-mark, the MolProbity clash score (number of serious clashes per 1,000 atoms11) was reduced from an average of 18.0 to 7.0 (Fig. 2a). Other refinement approaches that use less stringent or no steric criteria gave higher average clash scores (Table 1 and Supplementary Table 3).

Third, a recent community-consensus analysis indicates that 92.4% of RNA backbone ‘suites’ (sets of two consecutive sugar puckers with five connecting backbone torsions) fall into 54 rotameric classes, many of which are correlated with unique functions12. Nonrotameric suites are thus potential fitting errors. ERRASER-PHENIX reduced the number of such outliers in 22 of 24 cases, and reduced the average outlier rate from 19% to 8% (Table 1, Fig. 2b and Supplementary Table 4). This result was notable because the

54-rotamer classification was not used during the Rosetta modeling. In high-resolution cases, the ERRASER-fitted conformer typically agreed better with the electron density as determined by visual inspection (Fig. 1b). For cases with medium to low resolution, where the starting and remodeled conformer fit the density equally well upon visual inspection, ERRASER-PHENIX gave substan-tially more rotameric conformers (Fig. 1c). As an additional test, we applied ERRASER during a recent RNA-puzzles blinded trial13 involving a protein-RNA complex. ERRASER-PHENIX changed a suite in the protein-binding kink-turn in the starting RNA template (2YGH), from an outlier to the ‘2[’ rotamer consistent with other kink-turn motifs12 (Fig. 1d), which was indeed recovered in the subsequently released crystal structure (3V7E).

Fourth, RNA sugar rings typically exhibit either 2′-endo or 3′-endo conformations, but crystallographic assignments of these puckers can be ambiguous. Although sugar pucker errors can be confi-dently identified using simple geometric criteria, finding alterna-tive error-free solutions remains difficult11. ERRASER-PHENIX reduced the mean pucker error rate from 5% to 0.2%, and gave zero pucker errors in 19 cases (Table 1, Fig. 2c and Supplementary Table 4). As an example with functional relevance, we fitted an adenosine in the active site of the group I ribozyme with dif-ferent puckers in independent crystallographic models from bacteriophage Twort (adenosine 119 in 1Y0Q) and Azoarcus sp. BH72 (adenosine 127 in 3BO3). This discrepancy also led to dif-ferent hydrogen bonding patterns between the adenosine’s 2′-OH group and the guanosine (ΩG) substrate of the ribozyme (Fig. 1e). ERRASER-PHENIX improved agreement between the Twort and Azoarcus models throughout the active site and gave the same

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figure � | Examples of geometric improvements by ERRASER-PHENIX. (a) Clash reduction in PDB structure 3R4F. Red dots, unfavorable clashes. Left, PDB data. Right, ERRASER-PHENIX data. (b–d) Backbone conformation improvement on nucleotides 62–64, chain A of PDB structure 1U8D (b), nucleotides 27–34, chain Q of PDB structure 2OIU (c) and nucleotides 33–36, chain A of PDB structure 2YGH (d). Rotamer assignments are shown as two-character codes at each suite12. ‘!!’ stands for outlier rotamers. Red, PDB data. Blue, ERRASER-PHENIX data. (e) Functionally relevant pucker correction on group I ribozyme models. Brown, PDB 1Y0Q. Cyan, PDB 3BO3. Left, PDB data. Right, ERRASER-PHENIX data. (f) Base-pair geometry improvement on nucleotides 1–6 and 66–71, chain A of 3P49. Left, PDB data. Right, ERRASER-PHENIX data.

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figure 2 | Improvements of the crystallographic models by ERRASER-PHENIX across the test cases. (a) Clash score. (b) Frequencies of outlier backbone rotamers. (c) Frequencies of outlier puckers. (d) Rfree factors. The dashed lines denote linear fits.

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2′-endo pucker conformation and hydrogen-bonding network (Fig. 1e), in agreement with recent double-mutant analyses of group I ribozyme14.

ERRASER-PHENIX also improved RNA base-pairing patterns with enhanced co-planarity and hydrogen-bonding geometry of interacting bases, as assessed by the automated base-pair assign-ment program MC-Annotate15 and illustrated here for a glycine riboswitch (3P49, Fig. 1f). Furthermore, ERRASER-PHENIX led to remodeled glycosidic bond torsions (syn versus anti χ), whose accuracy we confirmed in several cases (Supplementary Results, Supplementary Fig. 2 and Supplementary Tables 5, 6).

We also evaluated the fits of our models to the diffraction data using R and Rfree factors. Avoiding increases in Rfree, the correla-tion to set-aside diffraction data, is critical for preventing over-fitting of experimental data16. The ERRASER-PHENIX pipeline consistently decreased both R and Rfree, lowering Rfree in 22 of 24 cases. The average R factor dropped from 0.210 to 0.199 and average Rfree factor dropped from 0.255 to 0.243 (Table 1, Fig. 2d and Supplementary Tables 7, 8). Other methods gave the same or worse average Rfree. As a practical demonstration, we had applied ERRASER-PHENIX to a newly solved structure of subdomain IIa from the hepatitis C virus internal ribosome entry site17. The ERRASER-PHENIX model gave fewer errors in all MolProbity criteria and lower R and Rfree, and this model was therefore deposited into PDB as the final structure (3TZR).

As a separate independent assessment, we compared the simi-larity of remodeled low-resolution structures to original PDB-deposited models of high-resolution structures with the same sequences. We reasoned that pairs of models with the same sequences should give similar local conformations and that the higher-resolution models could be used as working references. For all 13 such cases (Table 1 and Supplementary Tables 9, 10), ERRASER-PHENIX remodeling gave low-resolution models with increased agreement in backbone torsions and sugar puckers to those in the deposited high-resolution models. In addition, we evaluated structures related by noncrystallographic symme-try or by internal homology and found that ERRASER improved their agreement in all tested cases (Supplementary Results and Supplementary Tables 11, 12).

We also tested the quality improvement for lower-resolution models by ERRASER-PHENIX by comparing six data sets with low diffraction resolution (3.20–3.69 Å) to five data sets with high diffraction resolution (1.90–2.21 Å). For the low-resolution data sets, ERRASER-PHENIX improved the mean clash score from 40.8 to 7.9, which was lower than the mean clash score of 9.3 in the original high-resolution models. This value (7.9) is equal to the median clash score for models solved at 1.8 Å in a recent whole-PDB survey4. Similar reductions in outlier bond lengths and angles, outlier backbone rotamers and anomalous sugar puck-ers were apparent (Supplementary Tables 2–4).

For RNA crystallographic data sets across a wide range of resolutions and molecular size, ERRASER-PHENIX led consist-ent and substantial reduction of geometric errors, as assessed by independent validation tools and, in some cases, by independent functional evidence. The improved models gave similar or bet-ter fits to set-aside diffraction data in all cases. For all tested geometric features as well as R and Rfree values, the ERRASER-remodeled coordinates were significantly improved compared to starting PDB values across the benchmark (P < 0.02 by Wilcoxon

signed-rank test; Supplementary Table 13). Finally, comparison of remodeled low-resolution and independent high-resolution data sets indicated that this automated pipeline consistently increased the accuracy of RNA crystallographic models. We there-fore expect this algorithm to mark an application of ab initio RNA three-dimensional structure prediction that will be widely use-ful in experimental biology. ERRASER is available in the current Rosetta release (3.4) at http://www.rosettacommons.org/, as an online application through the Rosetta online server that includes everyone (ROSIE; http://rosie.rosettacommons.org/) and as a part of the PHENIX package (http://www.phenix-online.org/).

methodsMethods and any associated references are available in the online version of the paper.

Note: Supplementary information is available in the online version of the paper.

acknowledgmentsWe thank J.S. Richardson for suggesting this problem and for detailed evaluation of the results we used to improve the program; C.L. Zirbel and N.B. Leontis for suggestions on base pair validation; B. Stoner and D. Herschlag for discussions on group I ribozyme active site; T. Terwilliger and J. Headd for aid in integrating ERRASER into PHENIX; S. Lyskov for setting up the ERRASER protocol on the ROSIE Server; members of the Das lab for comments on the manuscript; and members of the Rosetta and the PHENIX communities for discussions and code sharing. Computations were performed on the BioX2 cluster (US National Science Foundation CNS-0619926) and the Extreme Science and Engineering Discovery Environment resources (US National Science Foundation OCI-1053575). This work was supported by funding from US National Institutes of Health (R21 GM102716 to R.D. and R01 AI72012 to T.H.), a Burroughs-Wellcome Career Award at Scientific Interface (R.D.), Governmental Scholarship for Study Abroad of Taiwan and Howard Hughes Medical Institute International Student Research Fellowship (F.-C.C.), and the C.V. Starr Asia/Pacific Stanford Graduate Fellowship (P.S.).

author contributionsF.-C.C., P.S. and R.D. designed the research. F.-C.C. implemented the methods and analyzed the results. P.S. provided code and assisted in data analysis. S.M.D. and T.H. provided the starting model and diffraction data of the unreleased 3TZR structure and evaluated its refinement. F.-C.C. and R.D. prepared the manuscript. All authors reviewed the manuscript.

comPeting financial interestsThe authors declare no competing financial interests.

Published online at http://www.nature.com/doifinder/�0.�0�8/nmeth.2262. reprints and permissions information is available online at http://www.nature.com/reprints/index.html.

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2. Gesteland, R.F., Cech, T. & Atkins, J.F. (eds.). The RNA World: The Nature of Modern RNA Suggests a Prebiotic RNA World. 3rd edn. (Cold Spring Harbor Laboratory Press, 2006).

3. Keating, K.S. & Pyle, A.M. Proc. Natl. Acad. Sci. USA �07, 8177–8182 (2010).4. Read, R.J. et al. Structure �9, 1395–1412 (2011).5. Wang, X. et al. J. Math. Biol. 56, 253–278 (2008).6. Das, R. & Baker, D. Proc. Natl. Acad. Sci. USA �04, 14664–14669 (2007).7. Das, R., Karanicolas, J. & Baker, D. Nat. Methods 7, 291–294 (2010).8. Sripakdeevong, P., Kladwang, W. & Das, R. Proc. Natl. Acad. Sci. USA �08,

20573–20578 (2011).9. DiMaio, F., Tyka, M.D., Baker, M.L., Chiu, W. & Baker, D. J. Mol. Biol. �92,

181–190 (2009).10. DiMaio, F. et al. Nature 47�, 540–543 (2011).11. Chen, V.B. et al. Acta Crystallogr. D Biol. Crystallogr. 66, 12–21 (2010).12. Richardson, J.S. et al. RNA �4, 465–481 (2008).13. Cruz, J.A. et al. RNA �8, 610–625 (2012).14. Forconi, M. et al. Angew. Chem. Int. Edn. 48, 7171–7175 (2009).15. Gendron, P., Lemieux, S. & Major, F. J. Mol. Biol. �08, 919–936 (2001).16. Brunger, A.T. Nature �55, 472–475 (1992).17. Dibrov, S.M. et al. Proc. Natl. Acad. Sci. USA �09, 5223–5228 (2012).

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online methodsOverview of the ERRASER-PHENIX pipeline. The ERRASER-PHENIX pipeline involves three major stages (Supplementary Fig. 1a). The starting model deposited in the PDB was first refined in PHENIX (v. dev-1034), with hydrogen atoms added. The refined model and electron-density map (setting aside the data for Rfree factor calculations; see below) were then passed into Rosetta (version r50831) for a three-step real-space refinement. First, all torsion angles and all backbone bond lengths and bond angles were subjected to continuous minimization under the Rosetta high-resolution energy function supplemented with electron density correlation score. The Rosetta all-atom energy function models hydrogen bonding, Lennard-Jones packing, solvation and torsional preferences, and has been successful in the modeling and design of RNA at near-atomic accuracy7,8. The electron density score term is similar to the Rosetta electron density score recently pioneered for application to electron cryomicroscopy and molec-ular replacement9,10. Second, bond length, bond angle, pucker and suite outliers were identified using phenix.rna_validate. In addition, we also included nucleotides that shifted substan-tially during the initial Rosetta minimization (evaluated by nucleotide-wise r.m.s. deviation before and after minimization). These outlier and high–r.m.s. deviation nucleotides were rebuilt by single-nucleotide stepwise assembly (SWA) in a one-by-one fashion, where all of a nucleotide’s atoms and the atoms up to the previous and next sugar were sampled by an exhaustive grid search of all torsions and a kinematic loop closure at sub- angstrom resolution (Supplementary Fig. 1b)8,18. If SWA found a lower-energy alternative structure of the rebuilt nucleotide, this new conformation was accepted. Third, the new model was mini-mized again in Rosetta. The rebuilding-minimization cycle was iterated three times to obtain the final ERRASER model. This model was again refined in PHENIX against diffraction data to obtain the final ERRASER-PHENIX model. All the ERRASER-PHENIX remodeled structures discussed in this paper are avail-able as Supplementary Data.

The new Rosetta module, ERRASER. The ERRASER protocol consisted of three steps: an initial whole-structure minimiza-tion, followed by single-nucleotide rebuilding and finally another whole-structure minimization. Before passing the models into ERRASER, the PHENIX-generated PDB files were converted to the Rosetta format. Protein components, ligands and modified nucleotides were removed from the model because current enu-merative Rosetta modeling only handles standard RNA nucleo-tides. To avoid anomalies in refitting, we held fixed the positions of the nucleotides that were bonded or in van der Waals con-tact with these removed atoms during the next ERRASER step. In 2OIU, a cyclic RNA structure, we also held fixed the first and the last nucleotides in the RNA chain to prevent the bonds from breaking during ERRASER. For structures that have notable interaction through crystal contacts, we manually included the interacting atoms in the ERRASER starting models.

Throughout the ERRASER refinement, an electron density score (unbiased by excluding set-aside Rfree reflections during map creation; see below) was added to the energy function to ensure that the rebuilt structural models retained a reasonable fit to the experimental data. The electron density scoring in our method is slightly different from the one published recently9,10.

Instead of calculating the density profile of the model every time we rescored the model, we precalculated the correlation between the density of a single atom and the experimental density in a fine grid. The score was defined as the negative of the sum of the atomic numbers of all the heavy atoms in the model times this rapidly computed real-space correlation coefficient. This new density scoring term, named ‘elec_dens_atomwise’, was an order of magnitude faster than the one in the previous Rosetta release, thus reducing the total computational time of our method substantially. To accommodate the change of our energy function caused by the electron density energy constraint, we also modified the weights in the original scoring function. The scoring weights file is included in the Rosetta release named ‘rna_hires_elec_dens.wts’.

In addition, we used a new RNA torsional potential for this study. This new potential was obtained by fitting to the logarithm of the histogram of RNA torsions derived from the RNA11 data set (http://kinemage.biochem.duke.edu/databases/rnadb.php). The RNA11 data set contains 24,842 RNA suites and 311 different PDB entries, which is much richer and more diverse than the 50S ribosomal subunit model (1JJ2, 2,875 suites) used in deriving the original potential7. This new potential can be turned on by includ-ing the tag “-score:rna_torsion_potential RNA11_based_new” in the Rosetta command line.

During the whole-structure minimization, we constrained the phosphate atoms in the RNA to their starting position; this is especially important for low-resolution models where the phos-phate positions were not accurately defined by electron density. Errors in phosphate positions were corrected during the latter rebuilding step. We also found that when the molecule was too large, Rosetta could not minimize the entire molecule because of slow scoring. Therefore for any molecule larger than 150 nucleo-tides, we decomposed the RNA into smaller segments with an automated script rna_decompose.py, and minimized each of them sequentially. To retain all interactions, we also included the nucleo-tides within 5 Å radius of the segment being minimized as fixed nucleotides during the minimization.

After the whole-structure minimization, we used PHENIX.rna_validate to analyze the obtained models. All nucleotides assigned to have outlier bond lengths, bond angles, puckers and/or potentially erroneous backbone rotamers (outliers or regular rotamers with suiteness < 0.1; suiteness is a quality measurement for rotamer assignments12) were identified as problematic and were rebuilt in subsequent Rosetta single-nucleotide rebuilding. Furthermore, because the single-nucleotide rebuilding region in Rosetta did not match the definition of a ‘suite’, we rebuilt both the selected nucleotide and the nucleotide preceding it to cover the whole suite for rotameric outliers.

In addition to rebuilding outlier nucleotides, we also computed the nucleotide-wise r.m.s. deviation between the models before and after minimization. The nucleotides with r.m.s. deviation larger than 0.05 times the diffraction resolution and within the 20% of the largest r.m.s. deviation nucleotides were also selected for rebuilding. We reasoned that because these nucleotides moved substantially after Rosetta minimization, their starting conforma-tions were not favorable in terms of Rosetta energy function and were potentially erroneous.

The single-nucleotide rebuilding step used in our method was based on a modified SWA algorithm in which the RNA chain was closed using triaxial kinematic loop closure18. For nucleotides

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at chain termini, the original SWA sampling was used because no chain closure was required. To rebuild nucleotides inside the RNA chain, we first created a chain break between O3′ and P in the lower suite of the rebuilding nucleotide. Then we sampled all possible torsion angles for εi, ξi, αi, αi + 1 in 20° steps, and the two most common conformation of the sugar pucker, 2′-endo and 3′-endo. For each sampled conformation, analytical loop clo-sure was applied to close the chain and determined the remaining six torsions (βi, γi, εi, ξi, βi + 1, γi + 1), which formed three pairs of pivot-sharing torsions. The glycosidic torsion χi and the 2′-OH torsion χi2′-OH were sampled after chain closure, and the generated models were further minimized in Rosetta. During the rebuilding, we applied a modest constraint to the glycosidic torsion so that it was more stable near the starting conformation; therefore only the base-orientation changes that gave substantial Rosetta energy bonuses were accepted as the final conformations. To reduce the computational expense, we only searched confor-mations that were within 3.0 Å r.m.s. deviation with respect to the starting models.

After the conformational search, 100 lowest-energy models were kept and additionally minimized under the constraint of the Rosetta ‘linear_chainbreak’ and ‘chainbreak’ energy term to ensure that the chain break was closed properly in the final model. Finally the best scored model was output as the new model for the RNA. If no new low-energy model could be found, then the program kept the start-ing model of that nucleotide. In the rebuilding process, the candi-date nucleotides were rebuilt sequentially from the 5′ end to 3′ end of the RNA sequence. To speed up the Rosetta rebuilding process, the nucleotide being rebuilt was cut out from the whole structural model together with all nucleotides with at least one atom within a 5-Å radius, rebuilt using SWA and pasted back to the model.

After all the problematic nucleotides were rebuilt, we mini-mized the whole model again to reduce any bond-length or angle errors that might have occurred in the rebuilding process and to improve the overall energy of the model. In this study, the rebuilding-minimization cycle was iterated three times, although single iterations gave nearly equivalent results (data not shown). The coordinates of the RNA atoms in the PHENIX model were then substituted by the new coordinates in the Rosetta-rebuilt model to give the final ERRASER output.

The three ERRASER steps discussed above were wrapped into a python script erraser.py and can be performed automatically. The user needs to input a starting pdb file, a ccp4 map file, the resolution of the map and a list of any nucleotides that should be held fixed during refinement due to their interaction with removed atoms.

A sample ERRASER command line used for the refinement of PDB 3IWN dataset is shown below:

erraser.py -pdb 3IWN.pdb -map 3IWN.ccp4

-map_reso 3.2 -fixed_res A37 A58-67 B137

B158-167

Here 3IWN.pdb is the name of the PHENIX refined model, 3IWN.ccp4 is the name of ccp4 density map file, -map_reso tag gives the resolution of the density map and -fixed_res specifies the nucleotides that should remain untouched. A37 means the 37th nucleotide of chain A in the pdb file.

Examples of the automatically generated Rosetta command lines by the python script are given in Supplementary Notes.

PHENIX refinement. PHENIX19 (v. dev-1034) was used for all the refinements performed in this study. We first prepared the starting models downloaded from the PDB for refinement using phenix.ready_set. This step added missing hydrogen atoms into the models and set up constraint files including ligand constraints and metal coordination constraints. For ligands A23, 1PE and CCC, we substituted the PHENIX-generated ligand constraints with constraint files from the CCP4 monomer library to achieve better geometry. Furthermore, phenix.ready_set did not auto-matically create bond-length and bond-angle constraints at the linkage between some modified nucleotides (GDP and GTP) and standard nucleotides, or between the first and the last nucleotide of a cyclic RNA. In such cases these constraints were added manu-ally. Finally, for pdb files with TLS (translation, libration, screw)20 refinement records, the TLS group information was manually extracted from the pdb files and saved in a separate file for fur-ther use in PHENIX.

After all the files for the refinement were ready, a four-step PHENIX refinement was performed. In the first step, because PHENIX does not load in TLS records in the pdb files, we per-formed a one-cycle TLS refinement to recover the TLS informa-tion. Second, the models were refined by phenix.refine for three cycles. At this step, ADP (atomic displacement parameters) weight (wxu_scale) was optimized by PHENIX using a grid search, and other parameters were manually determined based on the criteria described below. For higher-resolution structures, a higher wxc_scale (scale for X-ray versus sterochemistry weight) was found to be appropriate. Based on initial tests (on PDB cases 1Q9A and 2HOP, which were not included in this paper’s benchmark because they were used to set parameters), we used the following criteria: wxc_scale = 0.5 for resolution < 2.3 Å, wxc_scale = 0.1 for 2.3 Å ≤ resolution < 3 Å, wxc_scale = 0.05 for 3 Å ≤ resolu-tion ≤ 3.6 Å and wxc_scale = 0.03 for resolution > 3.6 Å. The ordered_solvent option (automatic water updating) was turned on for all structures. Empirically, we found that the real-space refinement strategy in PHENIX only gave equal or worse R factor, so it was turned off throughout all the refinement steps in this study. TLS refinement was turned on only for structures with TLS records in the deposited PDB files. Third, the models were further refined in phenix.refine for nine cycles using the same parameter set. Fourth, the models were additionally refined in phenix.refine for three cycles, with all target weights (wxc_scale and wxu_scale) optimized during the run. Other parameters remained the same as in the first refinement round. Finally, we compared the models by the three different refinement steps and selected the one with the best fit to the diffraction data as the final model. For 3OTO, the multistep PHENIX refinement clearly distorted the starting model and gave worse geometries, so in this case we used the results obtained after the first refinement step. For 3P49, we sup-plied 1URN as a reference model to improve the protein part of the structure during refinement21.

After the initial refinement, the electron density map was gen-erated from the experimental diffraction data and the PHENIX refined structural model for further ERRASER improvement. We used phenix.maps to create 2mFobs – DFcalc maps in ccp4 format, and diffraction data used for Rfree validation were excluded for the map generation to avoid directly fitting to the Rfree test set during ERRASER refinement. To avoid Fourier truncation errors resulting from the missing data, we filled any excluded or

http://www.rcsb.org/pdb/explore/explore.do?structureId=3IWNhttp://www.rcsb.org/pdb/explore/explore.do?structureId=1Q9Ahttp://www.rcsb.org/pdb/explore/explore.do?structureId=2HOPhttp://www.rcsb.org/pdb/explore/explore.do?structureId=3P49http://www.rcsb.org/pdb/explore/explore.do?structureId=1URN

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nature methods doi:10.1038/nmeth.2262

missing Fobs values with Fcalc values during the map calculation. The averaged kicked map approach was also used to reduce the noise and model bias of the maps22.

The final PHENIX refinement, after the ERRASER steps, was similar to the starting refinement described above, with small variations. First, there was no need for an initial TLS refinement as the pdb files already had this information at this stage. Second, we ran phenix.ready_set again on the ERRASER model to gener-ate metal coordination constraints for refinements, in case the new model presented different metal coordination patterns than the starting one. The models were then refined using PHENIX in the same multistep fashion, with the same parameter sets.

Examples of the PHENIX command lines used in this work are given in Supplementary Notes.

Refinement of 3TZR, a new structure of subdomain IIa from the hepatitis C virus IRES domain. The refinement of the 3TZR model currently deposited in the PDB was performed at an earlier stage of this work using an earlier PHENIX version (v1.7.1-743). The initial coordinates for 3TZR were already well-refined in PHENIX, and we therefore maintained the settings from that ini-tial stage. In particular, during the PHENIX refinement, hydrogen atoms were not added to the model, and wxc_scale was set to 0.5. The final PHENIX refinement was performed using the same setting as the initial refinement.

R and Rfree calculation. For consistency, R and Rfree values of all the models were calculated using phenix.model_vs_data23. For the starting models, the PHENIX-calculated R and Rfree were generally similar to the values shown in the PDB header; both are reported in Supplementary Tables 7,8. In the main text, we reported PHENIX-calculated R and Rfree to permit compari-sons across the refinement benchmark.

Similarity analysis test. The similarities of the local geometries between similar structural models (Supplementary Tables 9–12) were evaluated as follows. If differences between the torsion angles (α, β, γ, δ, ε, ζ, χ) of each nucleotide pair were all smaller than 40°, the pair was counted as a similar nucleotide pair. If the difference of the δ angles of a nucleotide pair was smaller than 20°, the pair was assigned as having similar sugar pucker. Finally, r.m.s. deviations of all the torsion angles (in degrees) between the model pairs were calculated as an indicator of the model similarity in the torsional space.

Other tools. RNABC5 (v1.11) and RCrane.CLI3 (v1.01) were combined with PHENIX in the same manner as the ERRASER-PHENIX pipeline, by substituting the ERRASER stage with RNABC and RCrane, respectively. As RNABC rebuilt only one nucleotide per run, a python script was used to achieve auto-matic rebuilding of all nucleotides. The MolProbity11 analysis was performed using command line tools phenix.clashscore and phenix.rna_validate in the PHENIX package. MC-Annotate15 (v1.6.2) was used to assign base pairs in starting and refined models. All molecular images in this work were prepared using PyMol, except Figure 1a, which used MolProbity11 and KiNG (Kinemage, Next Generation)24.

18. Mandell, D.J., Coutsias, E.A. & Kortemme, T. Nat. Methods 6, 551–552 (2009).

19. Adams, P.D. et al. Acta Crystallogr. D Biol. Crystallogr. 66, 213–221 (2010).20. Winn, M.D., Isupov, M.N. & Murshudov, G.N. Acta Crystallogr. D Biol.

Crystallogr. 57, 122–133 (2001).21. Headd, J.J. et al. Acta Crystallogr. D Biol. Crystallogr. 68, 381–390 (2012).22. Praznikar, J., Afonine, P.V., Guncar, G., Adams, P.D. & Turk, D. Acta

Crystallogr. D Biol. Crystallogr. 65, 921–931 (2009).23. Afonine, P.V. et al. J. Appl. Cryst. 4�, 669–676 (2010).24. Chen, V.B., Davis, I.W. & Richardson, D.C. Protein Sci. �8, 2403–2409 (2009).

http://www.rcsb.org/pdb/explore/explore.do?structureId=3TZRhttp://www.rcsb.org/pdb/explore/explore.do?structureId=3TZR

Supplementary Information

Correcting pervasive errors in RNA crystallography through

enumerative structure prediction Fang-Chieh Chou, Parin Sripakdeevong, Sergey M. Dibrov, Thomas Hermann & Rhiju Das*

Supplementary Item Title Supplementary Figure 1 ERRASER-PHENIX algorithm. Supplementary Figure 2 Base orientation improvements. Supplementary Table 1 Benchmark test set of 24 structural models, sorted by resolution.

Supplementary Table 2 Outlier bond lengths and angles of the benchmark assessed by phenix.rna_validate. Supplementary Table 3 Clashscore of the benchmark assessed by phenix.clashscore.

Supplementary Table 4 Outlier backbone rotamers and potentially incorrect sugar puckers of the benchmark assessed by phenix.rna_validate. Supplementary Table 5 Number of base-pairs identified by MC-Annotate. Supplementary Table 6 Summary of notable changes of base orientations (χ angle). Supplementary Table 7 R factors of the benchmark. Supplementary Table 8 Rfree factors of the benchmark.

Supplementary Table 9 Similarity analysis between high-resolution and low-resolution models.

Supplementary Table 10 Torsional RMSDs (in degrees) between high-resolution and low-resolution models. Supplementary Table 11 Similarity analysis for model pairs of the same or similar sequences.

Supplementary Table 12 Torsional RMSDs (in degrees) for model pairs of the same or similar sequences.

Supplementary Table 13 P-values of Wilcoxon signed-rank test between each method and the starting PDB dataset for all geometric features, R and Rfree. Supplementary Results Supplementary Notes

Nature Methods doi:10/1038/nmeth.2262

Supplementary Figure 1. ERRASER-PHENIX algorithm. (a) Flow chart of the whole pipeline, the ERRASER steps are enclosed in red. (b) Enumerative RNA modeling in Rosetta steps. The blue torsions are explicitly sampled by enumeration and the green torsions are determined by automatic loop closure.

Refine the starting PDB in PHENIX

Electron-density-guided whole structure minimization

Rebuild problematic nucleotides one at a time using Stepwise Assembly

Final PHENIX refinement

Electron-density-guided whole structure minimization

ERRASERSteps

Iterate

b

a


Supplementary Figure 2. Base orientation improvements. (a) Probability distribution of the χ angle in RNA09 (http://kinemage.biochem.duke.edu/databases/rnadb.php). The vertical lines show the range of syn vs. anti. Red: Purine; Blue: Pyrimidine; Dotted lines: 20X zoom-in of the distributions. (b) Base orientation changes in 2CKY, chain A, residue U35. Red: PDB model; Blue: ERRASER-PHENIX model; Brown: Reference model. (c, d) Base orientation changes in the ribosomal subunit 3OTO for residue (c) G266 and (d) U365. Red: PDB model; Blue: ERRASER-PHENIX model; Brown: Reference model (2VQE). Upper panel: Plot with electron density from 3OTO. Lower panel: Plot with electron density from 2VQE; the ERRASER model is aligned to the 2VQE model.

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

-180 -120 -60 0 60 120 180

Prob

ability

χ (degree)

SynAntia b

c d


Supplementary Table 1. Benchmark test set of 24 structural models, sorted by resolution.

PDB ID Name RNA lengtha Resolution (Å)

2A43 RNA Pseudoknot 26 1.34

3DIL Lysine Riboswitch 174 1.9

1U8D Guanine Riboswitch 68 1.95

3D2V Eukaryotic TPP Riboswitch 77 × 2 2

2GDI E. coli. TPP Riboswitch 80 × 2 2.05

3TZR HCV IRES Subdomain IIa 36 2.21

3MXH c-di-GMP Riboswitch 92 2.3

2PN4 HCV IRES Subdomain IIa 44 × 2 2.32

2QUS Hammerhead Ribozyme 69 × 2 2.4

1Y27 Guanine Riboswitch 68 2.4

2OIU L1 Ribozyme Ligase 71 × 2 2.6

2YGH SAM-I Riboswitch 95 2.6

3DIZ Lysine Riboswitch 174 2.85

3E5E SAM-III Riboswitch 53 2.9

2GIS SAM-I Riboswitch 94 2.9

2CKY Eukaryotic TPP Riboswitch 77 × 2 2.9

2PN3 HCV IRES Subdomain IIa 44 2.9

3F2Q FMN Riboswitch 112 2.95

3IWN c-di-GMP Riboswitch 93 × 2 3.2

3BO3 Azoarcus Group I Ribozyme 212 3.4

3R4F Prohead RNA 66 3.5

3P49 Glycine Riboswitch 169 3.55

1Y0Q Twort Group I Ribozyme 233 3.6

3OTO 30S Ribosomal Subunit 1,522 3.69 a The length of RNA component of the molecule. “× 2” indicates 2 copies in the asymmetric unit.


Supplementary Table 2. Outlier bond lengths and angles of the benchmark assessed by phenix.rna_validate.

PDB ID Outlier bonds(%) Outlier angles(%)

PDB PHENIX RNABC-PHENIX RCrane-PHENIX

ERRASER-PHENIX PDB PHENIX

RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

2A43 0 0 0 0 0 0 0 0 0 0

3DIL 0 0 0 0 0 0 0 0 0 0

1U8D 0 0 0 0 0 2.99 0 0 0 0

3D2V 0 0 0 0 0 0 0 0 0 0

2GDI 0 0 0 0 0 0 0 0 0 0

3TZR 0 0 0 0 0 0 0 0 2.78 0

3MXH 0 0 0 0 0 0 0 0 0 0

2PN4 2.38 0 0 0 0 2.38 0 0 0 0

2QUS 1.47 0 0 0 0 3.68 0.74 0 0 0

1Y27 0 0 0 0 0 4.48 0 0 0 0

2OIU 2.11 0 0 0 0 0.7 0 0 0 0

2YGH 3.19 0 0 0 0 2.13 0 0 0 0

3DIZ 0 0 0 0 0 0 0 0 0 0

3E5E 1.92 0 0 0 0 0 0 0 0 0

2GIS 0 0 0 0 0 6.38 0 0 0 0

2CKY 1.3 0 0 0 0 0.65 0 0 0 0

2PN3 0 0 0 0 0 0 0 0 0 0

3F2Q 0 0 0 0 0 0 0 0 0 0

3IWN 0 0 0 0 0 4.3 0 0 0 0

3BO3 0.45 0 0 0 0 0 0 0 0 0

3R4F 0 0 0 0 0 0 0 0 0 0

3P49 0 0 0 0 0 0.59 0 0 0 0

1Y0Q 0 0 0 0 0 0 0 0 0 0

3OTO 0 0.2 0.27 0.07 0 0 0.07 0 0.13 0

Average 0.53 0.01 0.01 0.003 0 1.18 0.03 0 0.12 0

Avg. high-resa 0 0 0 0 0 0.60 0 0 0.56 0

Avg. low-resb 0.08 0.03 0.05 0.01 0 0.82 0.01 0 0.02 0 Equal to or better than

PDB 23 / 24 23 / 24 23 / 24 24 / 24 23 / 24 24 / 24 22 / 24 24 / 24

Bond lengths and angles that have a deviation > 4 σ compared to PHENIX ideal geometry are counted as outliers. a Average value for the five high resolution models 3DIL, 1U8D, 3D2V, 2GDI and 3TZR. Ultra-high resolution dataset 2A43 was excluded. b Average value for the six lowest resolution models 3IWN, 3BO3, 3R4F, 3P49, 1Y0Q and 3OTO.


Supplementary Table 3. Clashscore of the benchmark assessed by phenix.clashscore.

PDB ID PDB PHENIX RNABC-PHENIX RCrane-PHENIX

ERRASER-PHENIX

2A43 1.19 1.19 2.38 2.38 1.19

3DIL 1.40 6.29 5.94 5.94 5.94

1U8D 14.02 16.22 13.59 12.71 10.08

3D2V 11.43 8.67 8.47 10.84 8.47

2GDI 5.52 8.41 8.98 8.60 6.50

3TZR 14.24 13.40 14.24 14.24 9.21

3MXH 8.48 5.58 6.69 8.93 6.92

2PN4 2.48 5.31 8.85 9.21 6.02

2QUS 12.97 13.43 10.52 12.75 6.71

1Y27 6.82 10.00 6.36 5.91 7.27

2OIU 8.48 7.61 7.61 9.13 5.00

2YGH 6.78 4.53 7.11 5.16 4.85

3DIZ 6.17 7.40 7.05 12.34 7.23

3E5E 4.51 4.53 2.83 9.07 5.09

2GIS 43.14 23.39 22.75 9.29 8.01

2CKY 20.47 12.99 11.22 10.83 7.68

2PN3 9.94 7.81 7.10 7.81 8.52

3F2Q 9.74 7.80 8.91 6.40 5.85

3IWN 55.65 23.31 19.63 13.94 12.71

3BO3 11.05 13.35 15.61 12.56 16.23

3R4F 49.62 16.07 15.12 16.54 10.85

3P49 17.56 5.43 6.57 7.43 3.00

1Y0Q 69.53 20.44 7.96 16.19 2.39

3OTO 41.42 15.75 15.30 14.69 3.17

Average 18.03 10.79 10.03 10.12 7.04

Avg. high-resa 9.32 10.60 10.24 10.47 8.04

Avg. low-resb 40.81 15.73 13.37 13.56 8.06

Equal to or better than PDB 15 / 24 17 / 24 15 / 24 17 / 24 Clashscore is the number of serious clashes (atom-pairs that have steric overlaps ≥ 0.4 Å) per 1,000 atoms. a Average value for the five high resolution models 3DIL, 1U8D, 3D2V, 2GDI and 3TZR. Ultra-high resolution dataset 2A43 was excluded. b Average value for the six lowest resolution models 3IWN, 3BO3, 3R4F, 3P49, 1Y0Q and 3OTO.


Supplementary Table 4. Outlier backbone rotamers and potentially incorrect sugar puckers of the benchmark assessed by phenix.rna_validate.

PDB ID Outlier backbone rotamers Potentially incorrect puckers



RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

2A43 1 1 1 3 2 0 0 0 0 0

3DIL 17 13 14 11 11 4 2 1 0 0

1U8D 4 5 7 3 2 3 2 2 0 0

3D2V 23 25 26 18 23 5 2 2 2 3

2GDI 22 17 16 14 11 8 2 2 3 0

3TZR 5 5 5 3 3 1 1 1 0 0

3MXH 8 9 10 11 11 2 1 1 0 0

2PN4 5 2 1 1 0 1 0 0 0 0

2QUS 35 26 24 18 17 9 6 6 2 0

1Y27 13 10 8 2 2 4 2 2 0 0

2OIU 29 17 17 8 6 6 0 0 0 0

2YGH 8 7 8 5 3 1 0 0 0 0

3DIZ 26 19 17 11 12 5 1 1 0 0

3E5E 6 6 5 4 4 2 1 1 0 0

2GIS 21 16 20 14 6 8 7 7 1 0

2CKY 64 44 37 21 18 18 5 5 2 2

2PN3 7 2 2 2 3 1 0 0 0 0

3F2Q 21 15 15 9 3 3 2 2 2 0

3IWN 52 42 42 29 27 23 12 11 4 2

3BO3 78 70 63 22 19 15 6 6 1 0

3R4F 16 13 17 10 6 5 1 1 1 0

3P49 73 57 60 31 22 19 11 11 8 1

1Y0Q 52 59 58 55 21 20 14 11 8 0

3OTO 279 301 313 253 145 34 35 37 27 0

Average (%)a 18.8 15.2 15.3 10.3 7.9 5.0 2.4 2.4 1.0 0.2

Avg. high-resb 11.7 11.2 11.9 8.0 7.9 3.6 1.9 1.8 0.6 0.4

Avg. low-resc 28.6 25.6 26.4 16.6 10.7 8.1 4.3 4.0 2.3 0.3 Equal to or better than

PDB 19 / 24 18 / 24 21 / 24 22 / 24 23 / 24 23 / 24 24 / 24 24 / 24

The backbone rotamer assignment is an effort of RNA Ontology Consortium1. Sugar pucker errors are determined using a geometric criterion based on the distance between the glycosidic bond vector (C1′–N1/9) and the following (3′) phosphate2. a Average error rate as percentage. Obtained by dividing the number of outliers with the total number of nucleotides. b Average value for the five high resolution models 3DIL, 1U8D, 3D2V, 2GDI and 3TZR. Ultra-high resolution dataset 2A43 was excluded. The values are normalized by the numbers of nucleotides in the models. c Average value (normalized) for the six lowest resolution models 3IWN, 3BO3, 3R4F, 3P49, 1Y0Q and 3OTO.


Supplementary Table 5. Number of base-pairs identified by MC-Annotate.

PDB ID PDB PHENIX RNABC-PHENIX RCrane-PHENIX

ERRASER-PHENIX

2A43 12 12 12 12 12

3DIL 88 89 89 90 91

1U8D 31 32 32 32 32

3D2V 69 68 68 69 68

2GDI 70 70 70 71 70

3TZR 15 15 15 15 15

3MXH 38 40 40 38 40

2PN4 32 32 32 32 32

2QUS 52 52 51 52 52

1Y27 36 34 35 34 36

2OIU 60 63 62 62 64

2YGH 37 37 37 39 43

3DIZ 88 89 89 89 88

3E5E 20 20 20 20 21

2GIS 40 36 38 37 40

2CKY 70 67 67 66 69

2PN3 16 17 16 16 16

3F2Q 43 44 44 44 44

3IWN 64 64 65 65 77

3BO3 86 85 81 85 92

3R4F 25 21 21 21 23

3P49 44 43 46 44 60

1Y0Q 97 89 87 92 104

3OTO 561 593 596 587 692

Average (%)a 83.4 82.7 82.7 82.8 87.0

Avg. high-resb 91.4 92.0 92.0 92.7 92.4

Avg. low-resc 72.2 69.4 69.3 70.1 81.5

Equal to or better than PDB 16 / 24 16 / 24 18 / 24 21 / 24 a Average value of (# of base-pairs) / (# of residues) × 2. The normalization is based on that the # of base-pairs in an ideal RNA duplex is half of the # of residues. b Average value calculated for the five high resolution models 3DIL, 1U8D, 3D2V, 2GDI and 3TZR. Ultra-high resolution dataset 2A43 was excluded. c Average value for the six lowest resolution models 3IWN, 3BO3, 3R4F, 3P49, 1Y0Q and 3OTO.


Supplementary Table 6. Summary of notable changes of base orientations (χ angle).

PDB ID Resolution Chain-Residue Base Type PDB ERRASER-PHENIX Reference

PDB Resolution Chain-Residue PDB

syn/anti χ syn/anti χ syn/anti χ

3DILa 1.9 A-110 G syn 75 anti -88 NA

3D2V 2 B-35 U syn 44 anti -123 3D2V 2 A-35 anti -110

2GDI 2.05 X-55 C anti -65 anti -160

NA Y-55 C syn 52 anti -135

2QUSb 2.4 A-22 G syn 97 anti -78

NA B-23 C syn 56 anti -119

2OIU 2.6 P-19 U syn 58 anti -136 2OIU 2.6 Q-19 anti -112

2YGH 2.6 A-14 A syn 41 anti -148 3GX5 2.4 A-9 anti -85

3DIZa 2.85 A-110 G syn 80 anti -85 NA

2CKY 2.9

A-1 G syn -7 anti 174

3D2V 2

A-1 anti -178

A-35 U syn 51 anti -116 A-35 anti -110

A-74 U syn 36 anti -167 A-74 anti -113

B-67 C syn -39 anti -129 B-67 anti -100

B-74 U anti -50 anti -140 B-74 anti -156

3IWN 3.2 A-7 C anti -51 anti -162

3MXH 2.3 R-17 anti -155

A-33 A anti -100 syn 82 R-33 syn 67

3BO3 3.4 B-21 C syn 91 anti -150 NA

3P49 3.55 A-731 C anti -58 anti -152

NA A-732 C syn -33 anti -129

1Y0Qc 3.6

A-35 A anti 150 anti -77

3BO3 3.4

NA

A-113 A syn 21 anti -176 B-121 anti 177

A-158 A syn 51 anti -152 B-134 anti -167

3OTO 3.69

A-91 C anti -58 anti -164

2VQE 2.5

A-91 anti -161

A-108 G syn -11 anti 180 A-108 syn 3

A-266 G anti -59 syn 54 A-266 anti -83

A-328 C syn 116 anti -85 A-328 syn 110

A-346 G syn 46 anti -143 A-346 syn 61

A-365 U syn 43 anti -157 A-365 syn 53

A-421 U syn 33 anti -134 A-421 syn 6

A-839 U syn 72 anti -164 A-839 syn 117

A-1004 A anti -87 syn 67 A-1004 anti -67

A-1054 C syn 81 anti -139 A-1054 syn 77

A-1279 A syn 43 anti -101 A-1279 syn 83

The table shows all the residues with Δχ > 90º upon ERRASER-PHENIX refinement. The definition of syn and anti conformation is: syn: -40 < χ ≤ 140; otherwise is anti. See supplementary results for discussion. a 3DIL and 3DIZ are structures of the same sequence with different resolution. However, ERRASER flipped residue 110 in both structure from syn to anti. Therefore we did not perform the high-resolution vs. low-resolution comparison in the table. b For 2QUS, the backbone conformations for residue 22-23 for chain A and chain B, as well as the structures of nearby region, are quite different. Therefore we did not use the different chains as reference models in our analysis. c 1Y0Q was compared to a homologous structure 3BO3. The two structures are group I ribozymes from different species. Residue 35 has no homologous partner in 3BO3 so was not compared.


Supplementary Table 7. R factors of the benchmark.

PDB ID PDB (Deposited) PDB

(PHENIX calculated) PHENIX RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

2A43 0.114 0.128 0.140 0.140 0.145 0.137

3DIL 0.192 0.183 0.172 0.169 0.171 0.170

1U8D 0.178 0.177 0.166 0.167 0.165 0.162

3D2V 0.207 0.202 0.212 0.210 0.224 0.211

2GDI 0.208 0.199 0.188 0.189 0.196 0.187

3TZR 0.182 0.182 0.184 0.185 0.188 0.180

3MXH 0.202 0.222 0.196 0.196 0.202 0.199

2PN4 0.261 0.258 0.264 0.270 0.268 0.264

2QUS 0.184 0.184 0.190 0.188 0.189 0.186

1Y27 0.232 0.224 0.204 0.205 0.207 0.203

2OIU 0.203 0.196 0.190 0.193 0.196 0.194

2YGH 0.200 0.186 0.197 0.206 0.199 0.205

3DIZ 0.193 0.200 0.198 0.201 0.203 0.202

3E5E 0.222 0.224 0.201 0.199 0.270 0.196

2GIS 0.266 0.249 0.216 0.219 0.218 0.216

2CKY 0.183 0.194 0.180 0.179 0.175 0.176

2PN3 0.229 0.214 0.213 0.212 0.239 0.210

3F2Q 0.200 0.197 0.199 0.202 0.202 0.200

3IWN 0.222 0.218 0.224 0.224 0.239 0.215

3BO3 0.282 0.266 0.244 0.240 0.274 0.239

3R4F 0.239 0.221 0.184 0.182 0.187 0.179

3P49 0.282 0.279 0.227 0.233 0.218 0.233

1Y0Qa 0.277 0.265 0.227 0.221 0.225 0.226

3OTO 0.173 0.177 0.163 0.164 0.163 0.186

Average 0.214 0.210 0.199 0.200 0.207 0.199

Avg. high-resa 0.193 0.188 0.185 0.184 0.189 0.182

Avg. low-resb 0.246 0.238 0.211 0.211 0.218 0.213

Equal to or better than PDB 16 / 24 15 / 24 12 / 24 16 / 24 a Average value for the five high resolution models 3DIL, 1U8D, 3D2V, 2GDI and 3TZR. Ultra-high resolution dataset 2A43 was excluded. b Average value for the six lowest resolution models 3IWN, 3BO3, 3R4F, 3P49, 1Y0Q and 3OTO.


Supplementary Table 8. Rfree factors of the benchmark.

PDB ID PDB (Deposited) PDB

(PHENIX calculated) PHENIX RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

2A43 0.190 0.180 0.166 0.165 0.176 0.162

3DIL 0.229 0.213 0.194 0.193 0.199 0.199

1U8D 0.228 0.218 0.198 0.202 0.202 0.198

3D2V 0.251 0.244 0.233 0.235 0.249 0.239

2GDI 0.241 0.229 0.216 0.219 0.219 0.217

3TZR 0.245 0.242 0.239 0.239 0.246 0.240

3MXH 0.239 0.270 0.231 0.233 0.239 0.235

2PN4 0.320 0.323 0.320 0.319 0.323 0.320

2QUS 0.253 0.253 0.235 0.231 0.234 0.225

1Y27 0.264 0.255 0.235 0.238 0.238 0.235

2OIU 0.238 0.233 0.224 0.225 0.225 0.224

2YGH 0.259 0.244 0.234 0.234 0.237 0.236

3DIZ 0.244 0.246 0.239 0.239 0.240 0.235

3E5E 0.259 0.258 0.254 0.256 0.348 0.261

2GIS 0.289 0.270 0.252 0.252 0.256 0.246

2CKY 0.250 0.253 0.236 0.235 0.231 0.234

2PN3 0.283 0.274 0.272 0.273 0.282 0.267

3F2Q 0.243 0.254 0.249 0.255 0.256 0.260

3IWN 0.292 0.287 0.282 0.281 0.297 0.270

3BO3 0.325 0.312 0.295 0.293 0.316 0.295

3R4F 0.271 0.252 0.245 0.241 0.243 0.239

3P49 0.310 0.299 0.290 0.279 0.280 0.295

1Y0Q 0.310 0.307 0.294 0.289 0.292 0.291

3OTO 0.231 0.232 0.225 0.225 0.223 0.233

Average 0.261 0.256 0.244 0.244 0.252 0.244

Avg. high-resa 0.239 0.229 0.216 0.218 0.223 0.219

Avg. low-resb 0.290 0.281 0.272 0.268 0.275 0.270

Equal to or better than PDB 24 / 24 24 / 24 17 / 24 21 / 24 a Average value for the five high resolution models 3DIL, 1U8D, 3D2V, 2GDI and 3TZR. Ultra-high resolution dataset 2A43 was excluded. b Average value for the six lowest resolution models 3IWN, 3BO3, 3R4F, 3P49, 1Y0Q and 3OTO.


Supplementary Table 9. Similarity analysis between high-resolution and low-resolution models.

High res.

models

Low res. models

Similar residues (%)a Similar puckers (%)b



RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

4FE5c 1U8D 87.5 87.5 87.5 89.1 92.2 98.4 96.9 96.9 98.4 100.0

4FE5c 1Y27 67.2 78.1 78.1 82.8 85.9 93.8 100.0 100.0 100.0 100.0

1U8D 1Y27 68.8 76.6 75.0 84.4 82.8 95.3 96.9 96.9 98.4 96.9

2YGH 2GIS 65.6 66.7 61.3 68.8 81.7 88.2 92.5 92.5 95.7 97.9

3DIL 3DIZ 94.3 93.7 92.5 85.1 94.8 98.9 98.9 98.9 98.9 98.3

3MXH 3IWN_1 53.3 54.6 55.8 61.0 71.4 85.7 92.2 92.2 89.6 94.8

3MXH 3IWN_2 45.5 49.4 48.1 50.7 63.6 81.8 90.9 90.9 89.6 90.9

3D2V_1 2CKY_1 57.1 71.4 72.7 66.2 79.2 85.7 96.1 96.1 94.8 97.4

3D2V_1 2CKY_2 42.9 64.9 67.5 74.0 75.3 89.6 97.4 97.4 97.4 94.8

3D2V_2 2CKY_1 54.6 61.0 62.3 63.6 77.9 92.2 100.0 100.0 98.7 100.0

3D2V_2 2CKY_2 45.5 59.7 64.9 68.8 71.4 90.9 98.7 97.4 97.4 97.4

2PN4_1 2PN3 77.3 84.1 81.8 86.4 86.4 95.5 97.7 97.7 93.2 97.7

2PN4_2 2PN3 84.1 84.1 86.4 81.8 84.1 93.2 95.5 95.5 93.2 95.5

Average 64.9 71.7 71.9 74.1 80.5 91.5 96.4 96.3 95.8 97.0

Equal to or better than PDB 12 / 13 11 / 13 11 / 13 13 / 13 12 / 13 12 / 13 12 / 13 12 / 13 a Nucleotide pair in which the differences between all torsion angles are smaller than 40°. b Nucleotide pair in which the difference between δ angle is smaller than 20°. c 4FE5 is a ultra-high resolution (1.32 Å) guanine riboswitch structure not in the benchmark set.


Supplementary Table 10. Torsional RMSDs (in degrees) between high-resolution and low-resolution models. High res. models

Low res. models PDB PHENIX

RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

4FE5 1U8D 25.1 24.5 25.8 21.5 15.3

4FE5 1Y27 39.3 36.7 33.5 33.2 30.5

1U8D 1Y27 37.3 35.1 32.0 30.3 31.4

2YGH 2GIS 38.4 37.7 38.2 32.2 29.0

3DIL 3DIZ 13.5 12.8 13.4 26.2 16.4

3MXH 3IWN_1 48.0 45.6 44.2 41.3 37.3

3MXH 3IWN_2 51.9 49.5 48.8 48.2 42.2

3D2V_1 2CKY_1 41.0 38.7 37.5 38.7 33.0

3D2V_1 2CKY_2 40.9 37.4 35.1 33.8 35.2

3D2V_2 2CKY_1 42.6 39.5 38.6 38.8 31.5

3D2V_2 2CKY_2 42.7 40.2 39.7 37.2 36.9

2PN4_1 2PN3 25.0 21.7 21.8 23.6 23.8

2PN4_2 2PN3 24.5 22.9 22.7 22.8 23.9

Average 36.2 34.0 33.2 32.9 29.7

Equal to or better than PDB 13 / 13 12 / 13 12 / 13 12 / 13 RMSD is calculated between all the torsion angles in the model pair.


Supplementary Table 11. Similarity analysis for model pairs of the same or similar sequences.

Chain1 Chain 2 Similar residues (%)a Similar puckers (%)b



RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

2GDI_1 2GDI_2 78.8 86.1 86.1 86.1 86.1 97.5 100.0 100.0 98.7 98.7

2OIU_1 2OIU_2 42.3 53.5 57.8 63.4 69.0 87.3 94.4 94.4 94.4 95.8

2QUS_1 2QUS_2 60.9 75.4 75.4 75.4 81.2 92.8 94.2 94.2 94.2 94.2

3P49_1 3P49_2 50.7 50.7 53.3 58.4 68.8 94.8 97.4 97.4 97.4 92.2

1U8D 1Y27 77.9 77.9 80.5 88.3 87.0 97.4 98.7 98.7 97.4 97.4

2YGH 2GIS 59.7 71.4 72.7 84.4 84.4 90.9 98.7 98.7 98.7 98.7

3DIL 3DIZ 86.4 90.9 88.6 90.9 90.9 97.7 97.7 97.7 97.7 97.7

3MXH 3IWN_1 34.2 39.5 34.2 68.4 73.7 84.2 94.7 92.1 94.7 100.0

3MXH 3IWN_2 68.8 78.1 82.8 85.9 84.4 95.3 100.0 100.0 100.0 100.0

3IWN_1 3IWN_2 65.6 71.0 66.7 71.0 89.3 88.2 93.6 93.6 95.7 97.9

3D2V_1 3D2V_2 94.3 95.4 94.8 92.5 97.7 98.9 100.0 100.0 100.0 100.0

3D2V_1 2CKY_1 53.3 55.8 54.6 64.9 72.7 85.7 92.2 92.2 92.2 96.1

3D2V_1 2CKY_2 45.5 48.1 49.4 55.8 62.3 81.8 92.2 92.2 93.5 90.9

3D2V_2 2CKY_1 57.1 70.1 70.1 77.9 85.7 85.7 98.7 98.7 98.7 98.7

3D2V_2 2CKY_2 42.9 64.9 70.1 79.2 77.9 89.6 100.0 100.0 100.0 97.4

2CKY_1 2CKY_2 54.6 63.6 64.9 79.2 83.1 92.2 100.0 100.0 98.7 98.7

2PN4_1 2PN4_2 45.5 62.3 64.9 77.9 74.0 90.9 98.7 98.7 97.4 100.0

2PN4_1 2PN3 77.3 81.8 79.6 84.1 81.8 95.5 97.7 97.7 93.2 97.7

2PN4_2 2PN3 84.1 84.1 86.4 93.2 86.4 93.2 95.5 95.5 95.5 95.5

Average 62.1 69.5 70.2 77.7 80.9 91.6 97.1 96.9 96.7 97.2

Equal to or better than PDB 19 / 19 19 / 19 18 / 19 19 / 19 19 / 19 19 / 19 18 / 19 18 / 19 a Nucleotide pair in which the differences between all torsion angles are smaller than 40°. b Nucleotide pair in which the difference between δ angle is smaller than 20°.


Supplementary Table 12. Torsional RMSDs (in degrees) for model pairs of the same or similar sequences. Chain 1 Chain 2 PDB PHENIX RNABC-PHENIX

RCrane-PHENIX

ERRASER-PHENIX

2GDI_1 2GDI_2 25.0 23.4 23.4 24.3 22.8

2OIU_1 2OIU_2 44.5 41.7 39.8 39.9 34.6

2QUS_1 2QUS_2 46.6 42.3 40.4 32.5 29.0

3P49_1 3P49_2 42.5 41.6 40.8 36.1 38.5

1U8D 1Y27 31.6 31.4 25.3 19.4 22.2

2YGH 2GIS 32.1 31.9 32.0 24.5 23.2

3DIL 3DIZ 19.2 17.5 22.4 17.7 16.4

3MXH 3IWN_1 50.9 49.7 51.7 37.0 32.9

3MXH 3IWN_2 37.3 34.4 26.0 28.2 28.8

3IWN_1 3IWN_2 38.4 37.4 37.5 30.5 22.1

3D2V_1 3D2V_2 13.5 12.0 11.7 19.5 11.7

3D2V_1 2CKY_1 48.0 45.6 44.0 38.0 37.3

3D2V_1 2CKY_2 51.9 49.4 46.7 42.1 42.5

3D2V_2 2CKY_1 41.0 38.5 35.1 31.4 27.6

3D2V_2 2CKY_2 40.9 36.9 30.8 27.3 31.9

2CKY_1 2CKY_2 42.6 39.6 37.8 27.5 24.9

2PN4_1 2PN4_2 42.7 40.3 37.8 27.5 31.0

2PN4_1 2PN3 25.0 21.2 26.7 24.1 22.2

2PN4_2 2PN3 24.5 21.3 20.0 16.5 20.2

Average 36.7 34.5 33.2 28.6 27.4

Equal to or better than PDB 19 / 19 16 / 19 18 / 19 19 / 19 RMSD is calculated between all the torsion angles in the model pair.


Supplementary Table 13. P-values of Wilcoxon signed-rank test between each method and the starting PDB dataset for all geometric features, R and Rfree.

Outlier bond Outlier angle Clashscore Outlier

backbone rotamer

Potentially incorrect pucker

Number of base-pairs R Rfree

PHENIX 0.017 0.004 0.089 0.001 < 0.001 0.521 0.009 < 0.001

RNABC -PHENIX 0.017 0.005 0.045 0.007 < 0.001 0.394 0.024 < 0.001

RCrane -PHENIX 0.017 0.015 0.136 < 0.001 < 0.001 0.733 0.450 0.014

ERRASER -PHENIX 0.018 0.005 0.006 < 0.001 < 0.001 0.009 0.011 < 0.001

The Wilcocon signed-rank test is a non-parametric statistical test for pairs of related samples. The test can tell whether two datasets are significantly different from each other. Therefore it is suitable for the comparison between the PDB-deposited values and values after improvement methods. Here the two-sided P-value for each comparison is given in the table. All data in the benchmark (n = 24) are used for the analysis. Calculations are performed with the python library SciPy.


Supplementary Results

ERRASER-PHENIX improves RNA base-pairing geometry

ERRASER-PHENIX visually improved the base pairing patterns of the RNA models, enhancing

the co-planarity of interacting bases. For example, Figure 1f shows a helical region in 3P49, a

structure solved at 3.55 Å resolution. At this resolution, accurate positioning of base planes into

the electron density map was difficult. Manual fits gave base pairs that were buckled or twisted

compared to geometries seen in higher-resolution crystallographic models3. RNABC and RCrane

held the base positions fixed during rebuilding and were thus unable to improve the base-pair

planarity. On the other hand, ERRASER-PHENIX improved the planarity of the base-pairs,

likely due to the hydrogen bonding potential included in the Rosetta energy function.

Independent base-pair validation tools – which, like MolProbity, would permit unbiased

assessment of improvement – are not currently available. However, we applied the base-pair

assignment method MC-Annotate4 and noted that the refined structures gave a higher number of

automatically assigned base-pairs than the starting PDB models in 21 out of 24 cases

(Supplementary Table 5). For the 3P49 case, ERRASER-PHENIX increased the number of base-

pairs from 44 in the PDB model to 60. Other methods (RNABC-PHENIX and RCrane-PHENIX)

lead to smaller improvements in this case, giving 46 and 44 base-pairs respectively.

ERRASER-PHENIX improves the base orientation

In addition to the base-pairing geometry improvement described above, ERRASER also

improved the orientation of bases in the models. The glycosidic torsions in a RNA structure

predominantly adopt two distinct conformations: syn and anti5. These two conformations can be

distinguished by the value of χ torsion angle of the glycosidic bond. In the discussion below, the


syn conformation is defined as -40º < χ ≤ 140º, and the remaining angle ranges are defined as

anti, based on the distribution of χ angles in RNA09 dataset (Supplementary Fig. 2a,

http://kinemage.biochem.duke.edu/databases/rnadb.php). It is also evident that the anti

conformation is much more probable than syn conformation, and syn pyrimidine conformers are

especially rare. Therefore in the current single-nucleotide rebuilding scheme, syn pyrimidine

conformers were sampled only if the starting model adopts syn conformation.

Supplementary Table 6 summarized all the notable base orientation changes (Δχ > 90 º) in the

benchmark. While most of the changes are syn-to-anti flips, in agreement with the higher

frequency of anti conformations, there are still a few anti-to-syn flips, confirming that

ERRASER did not blindly flip the base orientation from syn to anti. To evaluate the confidence

of these remodeled bases, these changes were compared to reference models of similar or higher

resolution with same or similar sequence. If such models were not available, and there were two

different copies of structures in one asymmetric unit, the different copy (to which the target

nucleotide did not belong) was used as reference model. For all test cases where reference

models are available except for the ribosome, all 12 base orientation changes agreed well with

the reference. In some cases these orientation changes even introduced extra hydrogen bonds,

further supporting these fixes (Supplementary Fig. 2b). For the lowest-resolution ribosome test

case (3OTO, 3.69 Å), most of the conformational changes did not match the higher-resolution

reference model (2VGE, 2.5 Å). However, since both structures were solved using molecular

replacement, it is possible that the two deposited structures inherited the same base orientations

from an earlier model6-7, therefore might share the same erroneous conformations. By detailed

inspection of the conformational changes, we found that the ERRASER changes in 3OTO gave

the same or more hydrogen bonds as the starting coordinates and agreed well with the electron


density. For example, Supplementary Figure 2c shows an example of such an orientation change

where a guanosine flipped from anti to syn and forming a Watson-Crick vs. Hoogsten base-pair

with two extra hydrogen bonds. The density map of higher-resolution model did not falsify the

possibility of this new, energetically more favorable conformation. On the other hand,

Supplementary Figure 2d demonstrates a case where the flipping is ambiguous, where a uridine

flipped from syn to anti, and both conformations have one hydrogen bond with nearby nucleotide.

Although the starting conformation fits slightly better in the higher-resolution density map

visually, it is possible that the alternative conformation also existed in the crystal structure with a

smaller occupancy. Across the benchmark, ERRASER-PHENIX gave improved, or at least

alternatively possible, conformations for the base orientations in RNA.

Pairwise comparison for models with similar sequences

Analogous to the independent comparison between remodeled low-resolution and original high-

resolution models (see the main text), we reasoned that pairs of models with the same or similar

RNA sequences should give similar conformations at corresponding nucleotides, and an accurate

refinement procedure should maintain or improve this similarity. We drew 19 such structural

pairs from three categories: models of the same sequences determined independently at different

resolutions (11 cases, same pairs as those used in high-res vs. low-res comparisons); two copies

present in the asymmetric unit related by non-crystallographic symmetry (7 cases); and the

conserved regions of two aptamer domains in glycine riboswitch (1 case). Supplementary Table

10-11 summarizes the results of the similarity comparison of the torsion angles of each

nucleotide pair, sugar pucker assignment and the RMSD in torsional space for these structure

pairs. In nearly all cases, ERRASER-PHENIX improved these metrics compared to the PDB

models, and gave better average values than RNABC-PHENIX and RCrane-PHENIX.


Supplementary Notes

Example Rosetta command lines used in ERRASER-PHENIX

(1) Full structure minimization.

erraser_minimizer. -native -out_pdb -score::weights rna/rna_hires_elec_dens -score:rna_torsion_potential RNA11_based_new –constrain_P true -vary_geometry true -fixed_res -edensity:mapfile -edensity:mapreso 2.0 -edensity:realign no

(2) Single nucleotide rebuilding with analytical chain closure.

swa_rna_analytical_closure. -algorithm rna_resample_test -s -native -out:file:silent blah.out -sampler_extra_syn_chi_rotamer true -sampler_extra_anti_chi_rotamer true -constraint_chi true -sampler_cluster_rmsd 0.1 -sampler_native_rmsd_screen true -sampler_native_screen_rmsd_cutoff 3.0 -sampler_num_pose_kept 100 -PBP_clustering_at_chain_closure true -allow_chain_boundary_jump_partner_right_at_fixed_BP true -add_virt_root true - rm_virt_phosphate true -sample_res 2 -cutpoint_closed 2 -fasta fasta -input_res 1 3-4 -fixed_res 1 3-4 -jump_point_pairs NOT_ASSERT_IN_FIXED_RES 1-4 -alignment_res 1-4 -rmsd_res 4 -score:weights rna/rna_hires_elec_dens -edensity:mapfile -edensity:mapreso 2.0 -edensity:realign no -score:rna_torsion_potential RNA11_based_new

(3) Single nucleotide rebuild at terminal nucleotides.

swa_rna_main. -algorithm rna_resample_test -s -native -out:file:silent blah.out -sampler_extra_syn_chi_rotamer true -sampler_extra_anti_chi_rotamer true -constraint_chi true -sampler_cluster_rmsd 0.1 -sampler_native_rmsd_screen true -sampler_native_screen_rmsd_cutoff 3.0 -sampler_num_pose_kept 100 -PBP_clustering_at_chain_closure true -allow_chain_boundary_jump_partner_right_at_fixed_BP true -add_virt_root true - rm_virt_phosphate true -sample_res 2 -cutpoint_closed 2 -fasta fasta -input_res 1-4 -fixed_res 2-4 -jump_point_pairs NOT_ASSERT_IN_FIXED_RES 1-4 -alignment_res 1-4


-rmsd_res 4 -score:weights rna/rna_hires_elec_dens -edensity:mapfile -edensity:mapreso 2.0 -edensity:realign no -score:rna_torsion_potential RNA11_based_new

Example PHENIX command lines used in ERRASER-PHENIX

(1) phenix.ready_set.

phenix.ready_set 3E5E.pdb

(2) One-cycle TLS refinement.

phenix.refine 2QUS-sf.mtz 2QUS.updated.pdb GTP.cif 2QUS.metal.edits 2QUS.link.edits tls.params main.number_of_macro_cycles=1 strategy=tls

(3) Three-cycle refinement with manual parameter set.

phenix.refine 2GIS-sf.mtz 2GIS.pdb 2GDI.metal.edits ordered_solvent=true optimize_adp_weight=true strategy=individual_sites+individual_adp+occupancies main.number_of_macro_cycles=3 wxc_scale=0.1

(4) Three-cycle refinement with automatically optimized target weight.

phenix.refine 2GIS-sf.mtz 2GIS_phenix_erraser_refine_001_refine_001.pdb 2GIS_phenix_erraser_refine_001_refine_001.metal.edits ordered_solvent=true optimize_adp_weight=true strategy=individual_sites+individual_adp+occupancies main.number_of_macro_cycles=3 optimize_xyz_weight=true

(5) Density map creation.

phenix.maps maps.params maps.params: ... map { map_type = 2mFo-DFc format = xplor *ccp4 file_name = 2GIS_cell.ccp4


kicked = True fill_missing_f_obs = True grid_resolution_factor = 1/4. region = selection *cell atom_selection = None atom_selection_buffer = 3 sharpening = False sharpening_b_factor = None exclude_free_r_reflections = True isotropize = True } ... 1. Richardson, J.S. et al. RNA backbone: Consensus all-angle conformers and modular string nomenclature

(an RNA Ontology Consortium contribution). RNA 14, 465-481 (2008). 2. Chen, V.B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Cryst.

D 66, 12-21 (2010). 3. Stombaugh, J., Zirbel, C.L., Westhof, E. & Leontis, N.B. Frequency and isostericity of RNA base pairs.

Nucleic Acids Res. 37, 2294-2312 (2009). 4. Gendron, P., Lemieux, S. & Major, F. Quantitative analysis of nucleic acid three-dimensional structures. J.

Mol. Biol. 308, 919-936 (2001). 5. Bloomfield, V.A. et al. Nucleic Acids: Structures, Properties, and Functions. (University Science Books,

2000). 6. Demirci, H. et al. Modification of 16S ribosomal RNA by the KsgA methyltransferase restructures the 30S

subunit to optimize ribosome function. RNA 16, 2319-2324 (2010). 7. Kurata, S. et al. Modified Uridines with C5-methylene Substituents at the First Position of the tRNA

Anticodon Stabilize U·G Wobble Pairing during Decoding. J. Biol. Chem. 283, 18801-18811 (2008).


Correcting pervasive errors in RNA crystallography through enumerative structure predictionMethodsONLINE METHODSOverview of the ERRASER-PHENIX pipeline.The new Rosetta module, ERRASER.PHENIX refinement.Refinement of 3TZR, a new structure of subdomain IIa from the hepatitis C virus IRES domain.R and Rfree calculation.Similarity analysis test.Other tools.

AcknowledgmentsAUTHOR CONTRIBUTIONSCOMPETING FINANCIAL INTERESTSReferencesFigure 1 Examples of geometric improvements by ERRASER-PHENIX.Figure 2 Improvements of the crystallographic models by ERRASER-PHENIX across the test cases.Table 1 | Average values for the validation results of the benchmark set

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